Search Results for "accelerator"
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Showing 121 open source projects for "accelerator"
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1
Tempesta FW
All-in-one solution for high performance web content delivery
Tempesta FW is an all-in-one open-source solution for high performance web content delivery and advanced protection against DDoS and web attacks. This is a drop-in-replacement for the whole web server frontend infrastructure: an HTTPS load balancer, a web accelerator, a DDoS mitigation system, and a web application firewall (WAF). Tempesta FW is the first and only hybrid of a Web accelerator and a multi-layer firewall. This unique architecture provides seamless integration with the Linux iptables or nftables. Tempesta FW services up to 1.8M HTTP requests per second on the cheapest hardware, which is x3 faster than Nginx or HAProxy. ... -
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ONNX Runtime
ONNX Runtime: cross-platform, high performance ML inferencing
ONNX Runtime is a cross-platform inference and training machine-learning accelerator. ONNX Runtime inference can enable faster customer experiences and lower costs, supporting models from deep learning frameworks such as PyTorch and TensorFlow/Keras as well as classical machine learning libraries such as scikit-learn, LightGBM, XGBoost, etc. ONNX Runtime is compatible with different hardware, drivers, and operating systems, and provides optimal performance by leveraging hardware accelerators where applicable alongside graph optimizations and transforms. ... -
3
ChatGLM3
ChatGLM3 series: Open Bilingual Chat LLMs | Open Source Bilingual Chat
...The repo ships Python APIs, CLI and web demos (Gradio/Streamlit), an OpenAI-format API server, and a compact fine-tuning kit. Quantization (4/8-bit), CPU/MPS support, and accelerator backends (TensorRT-LLM, OpenVINO, chatglm.cpp) enable lightweight local or edge deployment. -
4
NVTOP
GPU & Accelerator process monitoring for AMD, Apple, Huawei, Intel
NVTOP stands for Neat Video card TOP, a (h) top-like task monitor for GPUs and accelerators. It can handle multiple GPUs and print information about them in a htop-familiar way. Currently supported vendors are AMD (Linux AMD GPU driver), Apple (limited M1 & M2 support), Huawei (Ascend), Intel (Linux i915 driver), NVIDIA (Linux proprietary divers), and Qualcomm Adreno (Linux MSM driver). -
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5
Pilipala
Recommendations, live streams, video playback
PiliPala is a GPL‑licensed, Flutter-built third-party Bilibili client that works on Android, iOS, desktop, and web. It includes recommendations, live streams, video playback with gestures, adjustable playback speed, AV quality and decoder controls, bullet comments, subtitles, snapshots, fullscreen modes, UI theming, blacklists, and more. -
6
Frigate
NVR with realtime local object detection for IP cameras
Frigate - NVR With Realtime Object Detection for IP Cameras A complete and local NVR designed for Home Assistant with AI object detection. Uses OpenCV and Tensorflow to perform realtime object detection locally for IP cameras. Use of a Google Coral Accelerator is optional, but highly recommended. The Coral will outperform even the best CPUs and can process 100+ FPS with very little overhead. -
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tt-metal
TT-NN operator library, and TT-Metalium low level kernel programming
tt-metal, also referred to in its documentation as TT-Metalium, is Tenstorrent’s low-level software development kit for programming applications on Tenstorrent AI accelerators. The project is designed for developers who need direct access to the company’s Tensix processor architecture, exposing a programming model that is closer to hardware control than high-level inference frameworks. Instead of following a traditional GPU model centered on massive thread parallelism, the platform is built... -
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Denoising Diffusion Probabilistic Model
Implementation of Denoising Diffusion Probabilistic Model in Pytorch
Implementation of Denoising Diffusion Probabilistic Model in Pytorch. It is a new approach to generative modeling that may have the potential to rival GANs. It uses denoising score matching to estimate the gradient of the data distribution, followed by Langevin sampling to sample from the true distribution. If you simply want to pass in a folder name and the desired image dimensions, you can use the Trainer class to easily train a model. -
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Best-of Machine Learning with Python
A ranked list of awesome machine learning Python libraries
This curated list contains 900 awesome open-source projects with a total of 3.3M stars grouped into 34 categories. All projects are ranked by a project-quality score, which is calculated based on various metrics automatically collected from GitHub and different package managers. If you like to add or update projects, feel free to open an issue, submit a pull request, or directly edit the projects.yaml. Contributions are very welcome! General-purpose machine learning and deep learning... -
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10
Generative AI Examples
Generative AI Examples is a collection of GenAI examples
Efficiently integrate secure, performant, and cost-effective Generative AI workflows into business value. Detailed framework of composable building blocks for state-of-the-art generative AI systems including LLMs, data stores, and prompt engines. Architectural blueprints of retrieval-augmented generative AI component stack structure and end-to-end workflows. A four-step assessment for grading generative AI systems around performance, features, trustworthiness and enterprise-grade readiness. -
11
Summarize
Point at any URL/YouTube/Podcast or file
...The repository includes troubleshooting guidance for common extension and connectivity issues, which signals that the tool is intended for daily use rather than one-off demos. Overall, it positions itself as a practical “reading accelerator” that fits into both developer workflows and normal browsing habits. -
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XiangShan
Open-source high-performance RISC-V processor
XiangShan is an open-source, high-performance RISC-V processor project that implements out-of-order superscalar cores using Chisel for hardware construction. The design targets modern performance goals—deep pipelines, speculative execution, multi-issue decode/execute, and sophisticated branch prediction—while remaining synthesizable for ASIC flows and portable to FPGAs for research. A modular microarchitecture separates frontend, backend, and memory subsystems with coherent caches and... -
13
Diffrax
Numerical differential equation solvers in JAX
...The project provides tools for solving ordinary differential equations, stochastic differential equations, controlled differential equations, and related systems in a way that fits naturally into modern machine learning and differentiable programming workflows. Because it is written to work closely with JAX, it supports just-in-time compilation, automatic differentiation, vectorization, and accelerator-backed execution on hardware such as GPUs and TPUs. This makes it especially appealing for researchers who need equation solvers that can be embedded inside trainable models or simulation-heavy learning systems. -
14
Pathway AI Pipelines
Ready-to-run cloud templates for RAG
...The templates include built-in indexing, vector search, hybrid search, and caching capabilities that remove the need to assemble separate infrastructure components. Developers can run the applications locally or deploy them to cloud platforms using Docker with minimal setup. Overall, llm-app functions as a practical accelerator for teams building real-time, production-ready AI knowledge systems. -
15
MaxText
A simple, performant and scalable Jax LLM
...The project acts as both a reference implementation and a practical training library that demonstrates best practices for building and scaling transformer-based language models on modern accelerator hardware. It is optimized to run efficiently on Google Cloud TPUs and GPUs, enabling researchers and engineers to train models ranging from small experiments to extremely large distributed workloads. The framework focuses on simplicity while still supporting advanced techniques such as model sharding, distributed computation, and high-throughput training pipelines. ... -
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Colossal-AI
Making large AI models cheaper, faster and more accessible
The Transformer architecture has improved the performance of deep learning models in domains such as Computer Vision and Natural Language Processing. Together with better performance come larger model sizes. This imposes challenges to the memory wall of the current accelerator hardware such as GPU. It is never ideal to train large models such as Vision Transformer, BERT, and GPT on a single GPU or a single machine. There is an urgent demand to train models in a distributed environment. However, distributed training, especially model parallelism, often requires domain expertise in computer systems and architecture. ... -
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AWS EC2 FPGA
AWS EC2 FPGA hardware and software development Kit
...After creating an FPGA design (also called CL - Custom logic), developers can create an Amazon FPGA Image (AFI) and easily deploy it to an F1 instance. AFIs are reusable, shareable and can be deployed in a scalable and secure way. Development experience leverages an optimized compiler to allow easy new accelerator development or migration of existing C/C++/openCL, Verilog/VHDL to AWS FPGA instances. Fully custom hardware development experience provides hardware developers with the tools required for developing AFIs for AWS FPGA instances. -
18
DataHandlerP
Fusion and Analysis for Hyperspectral data
...The Data Handler P was developed at the CNRS Laboratory for Molecular and Structural Archaeology (LAMS) at the Sorbonne University in Paris (FR) in by Matthias Alfeld collaboration with Philippe Walter, Laurence de Viguerie and Marie Radepont. Later the code was revised and refined at the German Particle Accelerator (DESY, Hamburg, DE) and TU Delft (NL) by M. Alfeld. A publication of the source code and a video tutorial are in preparation. The current release is for gathering user feedback. A description of the modules can be found in the Wiki. -
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Free Download Manager
Powerful modern download accelerator and organizer for all platforms
Free Download Manager for Windows, macOS, Android, and Linux allows you to adjust traffic usage, organize downloads, control file priorities for torrents, efficiently download large files and resume broken downloads. Free Download Manager (FDM) is a versatile, user-friendly software that revolutionizes how users manage and accelerate their downloads. It seamlessly integrates with various browsers, making it an essential tool for anyone who downloads files frequently. FDM enhances download... -
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Hyper Download Manager
High-performance download manager with modern UI and browser support.
Hyper Download Manager (HDM) is a high-performance, open-source download accelerator engineered for speed, privacy, and simplicity. Built with Python and PySide6, it features a sleek, modern interface inspired by Windows 11 aesthetics that blends seamlessly with your desktop environment. HDM replaces your browser's default download manager, offering deep integration with Chrome, Edge, Brave, and Firefox through native messaging. -
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skunks
3D driving simulation based on Open Dynamics Engine
Sour*eforge.net has become inaccesible to me because of Cl*udflare. The latest version of skunks is on my site: https://matei.one/. 3D realistic driving (not racing) simulation with software rendering, based on Open Dynamics Engine (which is included in all *.tar.gz files so it doesn't have to be downloaded separately). 10 cars (all electric) and 16 tracks are available in version 5.1.0. Cars and tracks can be easily created and modified. Only SDL 1.2 or SDL 2 required besides standard C... -
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simple3d
realistic driving simulation + functions for 2D/3D graphics
Sour*eforge.net has become inaccesible to me because of Cl*udflare. The latest versions of the programs will be on my site: https://matei.one/. Simcar - driving (not racing) simulation, with stunts and realistic physics since version 5.0.0. GNU/Linux and Wind0w$ executables are available. SDL_grf - functions for 2D/3D graphics (including text), sound and input + a few programs for viewing 3D models, viewing ZX Spectrum *.scr files, simulating the Solar System etc. Simple3d - old program for... -
23
MMDeploy
OpenMMLab Model Deployment Framework
...All kinds of modules in the SDK can be extended, such as Transform for image processing, Net for Neural Network inference, Module for postprocessing and so on. Install and build your target backend. ONNX Runtime is a cross-platform inference and training accelerator compatible with many popular ML/DNN frameworks. Please read getting_started for the basic usage of MMDeploy. -
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The SPMS is a tool for event management tailored for accelerator conferences. See www.jacow.org for more information.
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Apple Neural Engine (ANE) Transformers
Reference implementation of the Transformer architecture optimized
...The project sits alongside related Apple ML repos that focus on deploying attention-based models efficiently to ANE-equipped hardware. In short, it’s a practical blueprint for adapting Transformers to Apple’s dedicated ML accelerator without rewriting entire model stacks.
